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DBMS > Faircom EDGE vs. Lovefield vs. Splice Machine vs. Tkrzw vs. Yaacomo

System Properties Comparison Faircom EDGE vs. Lovefield vs. Splice Machine vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonLovefield  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsEmbeddable relational database for web apps written in pure JavaScriptOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgegoogle.github.io/­lovefieldsplicemachine.comdbmx.net/­tkrzwyaacomo.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperFairCom CorporationGoogleSplice MachineMikio HirabayashiQ2WEB GmbH
Initial release19792014201420202009
Current releaseV3, October 20202.1.12, February 20173.1, March 20210.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaScriptJavaC++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-freeyes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like query language infovia JavaScript builder patternyesnoyes
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noyes infoJavano
TriggersyesUsing read-only observersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByesyes infousing specific database classesyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Faircom EDGE infoformerly c-treeEDGELovefieldSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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